MAP’s assisted microbiome engineering

Green revolution is considered as greatest landmark in the history of agriculture, as it has saved nearly 25 million hectare of land being converted to agriculture and prevented billions of peoples from starvation. However, over exploitation of agrochemicals like pesticides and chemical fertilizers have resulted in to sever health issues for example majority of peoples in Punjab region are suffering from cancer and other health problems. Also it has resulted in to pollution of water bodies and has detoriated quality of land and have degraded the soil health, thereby bringing unsustainability in long term. So, what can be the solution which can bring sustainability in medium to long term without affecting the natural ecosystem? Solution is Plant Microbiome, engineering plant microbiome by using diversity to grow more.

Review Article https://doi.org/10.20546/ijcmas.2019.805.089

MAP’s Assisted Microbiome Engineering Mayur Naitam* and T.V Abiraami

Division of Microbiology, ICAR- Indian Agriculture research Institute,

New Delhi-110012, India

*Corresponding author

A B S T R A C T

Introduction

Green revolution is considered as greatest

landmark in the history of agriculture, as it

has saved nearly 25 million hectare of land

being converted to agriculture and prevented

billions of peoples from starvation However,

over exploitation of agrochemicals like

pesticides and chemical fertilizers have

resulted in to sever health issues for example

majority of peoples in Punjab region are

suffering from cancer and other health

problems Also it has resulted in to pollution

of water bodies and has detoriated quality of

land and has degraded the soil health, thereby bringing unsustainability in long term So, what can be the solution which can bring sustainability in medium to long term without affecting the natural ecosystem? Solution is Plant Microbiome, engineering plant microbiome by using diversity to grow more Microbiome is a community of microorganisms (such as bacteria, fungi, and viruses) that inhabit a particular environment and especially the collection of microorganisms living in or on the plant, human or any living organism’s body Plant

International Journal of Current Microbiology and Applied Sciences

ISSN: 2319-7706 Volume 8 Number 05 (2019)

Journal homepage: http://www.ijcmas.com

Green revolution is considered as greatest landmark in the history of agriculture, as it has saved nearly 25 million hectare of land being converted to agriculture and prevented billions of peoples from starvation However, over exploitation of agrochemicals like pesticides and chemical fertilizers have resulted in to sever health issues for example majority of peoples in Punjab region are suffering from cancer and other health problems Also it has resulted in to pollution of water bodies and has detoriated quality of land and have degraded the soil health, thereby bringing unsustainability in long term

So, what can be the solution which can bring sustainability in medium to long term without affecting the natural ecosystem? Solution is Plant Microbiome, engineering plant microbiome by using diversity to grow more

K e y w o r d s

MAP’s,

Microbiome,

Green

revolution

Accepted:

10 April 2019

Available Online:

10 May 2019

Article Info

Microbiome comprises of the microbial

community which inhabits different plant

organs like, root (Rhizobiome), leaf, stem,

flower etc

microbiome comprises holobiont

Phytobiont: Plant along with its complete

microbiome is regarded as Phytobiome

naturally

Plant follows the following strategies:

Production of specific root exudates e.g

Malic acid, succinic acid

Secretion of secondary metabolites e.g

DIMBOA by maize plant

Exudation of signaling molecules e.g AHL

by Medicago trancatula

Plant genotype e.g Glucosinolates production

by transgenic Arabidopsis

Defense activation and recruitment in

response to infection e.g Firmicutes against

Ralstonia solanocearum

How we are shaping the microbiome till

date

Selection during domestication of crop plants

Plant breeding to change quality and quantity

of root exudates

Development of transgenic varieties

Bio-fertilizers: introduction on seed, planting

material or in soil

Foliar spray of nutrient, organic compound

and chemicals

Crop management practices

Soil type and properties

MAP’s in engineering plant microbiome

MAP’s stands for microbiome assisted

engineering It is qualitative and taxonomy

driven approach These emerging MAP’s

includes the traits like Plant growth, root

architecture, flowering time, drought

resilience and disease suppressiveness This taxonomic and functional basis of MAP’s can

be elucidated through amplicon sequencing, isolation and phenotypic screening and by using the shotgun omics approaches like Metagenomics, metatranscriptomics, Metaproteomics combined with the studies of metabolomics which will give a complete overview of metaphenome of a plant

Map’s assisted plant microbiome engineering involves two approaches First top down approach involves mathematical and experimental analysis for quantitative assessment of potential and ecological context

of MAP’s Unlike top down approach, bottoms up approach involves targeted analysis of host and microbes for identification of functional basis of MAP’s at molecular and biochemical level

MAP’s first approach

The main guiding principle in MAP’s first approach is going back to the roots which involves search for the missing plant microbes to restore the plant microbe interactions lost during domestication or during breeding for disease resistance This MAP’s first approach involves systematic quantification of most significant MAP’s across and wild and domesticated host, herein natural ecosystem, traditional and modern agriculture serves as reservoir of genetic and ecological potential, for identification of microbiome associated phenotypes These MAP’s are systematically screened for identification of plant microbe and environmental combinations in which MAP’s provide largest fitness advantage This framework will guide into the mechanism that drives MAP’s, and this generated information can be used for targeted plant breeding and microbiome engineering in concert with the plant genotype referred to as Next generation agriculture

Experimental basis of MAP’s

MAP’s are defined quantitatively, for

examples salt tolerance, phosphorus

solubilization, disease suppressiveness etc

but the contribution of MAP’s to fitness and

the conditions in which maximum benefits

from cumulative microbiome effect comes

should be assessed quantitatively These

studies will inform us about where to target

the mechanistic investigation, where to apply

direct microbiome engineering efforts and it

will also guide the field applications for

results generated and applications developed

Once a particular MAP has been determined,

it becomes necessary to access the cumulative

microbiome effect across range of conditions

to determine the effect on host in both germ

free and microbiome associated host states

For each conditions, fitness can be assessed

quantitatively using parameters such as yield,

number of lateral roots, chlorophyll content

etc This experimental basis or setup can be

used for studying the changes in the fitness of

host plant having similar genotype but

differing in their microbiome composition by

subtracting or removing the fitness of host in

germfree condition from the fitness of

microbiome associated host, which will

provide insights into the maximum

cumulative microbiome effect

A condition of Disbiosis can be observed in

the case of plants under differing salt

concentration, where the fitness of germfree

host plant is more compared to the fitness of

microbiome associated host plant This

condition of Disbiosis is the result of

disbalance in microbiome composition or

functioning causing negative effect on host

fitness and phenotypes Also this experiments

can be exploited for studying the effect of two

different microbiomes on the same plant

keeping all other parameters same

For successful adaptation of microbiome, taxonomic shift and functional changes are of critical concern This host guided selection experiments can provide insights into the additional parameters such as, holobiont recruitment rate and holobiont fitness stability Thus this experimental basis shows that optimizing variables such as, altered cumulative microbiome effect, holobiont recruitment rate and holobiont fitness stability, to achieve maximum fitness gain and rapid recruitment and stability are key objectives of engineering microbiome Based

on these findings targeted comparative analysis selects for most significant emergent MAP’s From microbial side analysis of functional and compositional enrichment and significant co-occurrence pattern can be used for design of synthetic microbial community The most significant microbial and plant traits combined with the Genome wide association studies, Exudate profiling, screening and preparation of isolate libraries along with holobiont omics and QTL analysis, will provide genetic, molecular, ecological and biochemical signatures for holobiont engineering

Modular microbiome What is module?

Discrete, individually separate and distinct, functional communities may be viewed as modules Modules can be combined to provide novel functional combinations, which are designed to increase the host fitness across the multiple niche dimensions Oyserman in

2016 provided the functional basis of modularity in microbiome when he tried to develop a novel waste water treatment by combining photosynthetic nitrifying group with polyphosphate accumulating organisms group The concept was to use the full potential of each functional guild’s unique

metabolic potential By designing such

biogeochemically complementary

communities or modules, the need for

mechanical aeration was overcomed and

polyphosphate cycling was not interrupted

From this experiment it becomes clear that,

the impact of different communities or

modules on the function is nonlinear Some

communities can be dominant with no

significant change in cumulative microbiome

effect and some are recessive with significant

change in cumulative microbiome effect after

mixing due to trade of between the two

functional MAP’s, which constitutes a

suboptimal space and this can be represented

by Pareto curve, such that increase in ∆A1

occurs with trade of or at the cost of decrease

in ∆A2 By designing the microbiome with

multiple modules, the slope of the Pareto

curve can be shifted such that, increase in

∆A1 and ∆A2 can be achieved with a cost to

the other

Successful implementation of microbial

communities as modular component requires,

firstly, minimizing the overlap in resource

requirement between the functional guilds,

example between endosphere and

rhizosphere Secondly minimizing the trade of

between the functional guilds, which will be

the key for developing customizable and

modular microbiome

Because there is no any silver bullet organism

which will provide an optimal MAP under all

environmental and ecological conditions,

modularity in microbiome would provide

agriculture with toolbox to rapidly adapt and

maximize the crop yield under diverse

environmental and ecological conditions

How the modularity in microbiome can be

achieved?

The impact of modular microbiome on fitness

can be quantified using the host guided

selection to find optimal positions in Map’s solution space by “changing the rules of the games” through, resource partitioning of the root exudates such that separate functional components of microbiome can coexist e.g Plant microbe cross feeding strategies in opine producing plants, which preferentially selects for opine catabolizing microbes and minimizes the cross talk with non-target microbes Alternatives can be

1 Breeding for tailored root exudates composition and designing functional microbial modules depending on these distinct exudate profiles

compartmentalization produced by rhizosphere, endosphere and phylloshpere communities

3 Engineering MAP heterogeneity at population level, can lead to intercompatibility between MAP’s without necessitating individual host level modularity

e g an approach analogous to intercropping can be adapted neighbors or interacting microbes provides combinatorial effect for the population

In context to going back to the roots, microbiome modularity may already be a trait

of many plants in the wild that faces changing conditions and natural selection, thus natural variation in host optimized genetically for millions of years by evolution may serve as yet untapped source for investigating microbiome modularity

Network analysis of the community structure may be used to identify such modules including hub taxa that can form central node

in the community network

Functional basis of modularity

As we know the plant microbe interactions are mediated by molecules secreted by plant and microbes both, which may include,

primary metabolites e.g Sugars and amino

acids, and secondary metabolites like

signaling and antimicrobial compounds They

may provide carbon source, complement

auxotrophy, attract, deter or act

antagonistically to dictate the microbiome

assembly process So to understand the

functional basis we first need to understand

the genetic basis and chemical interplay that

drives the MAP’s This study will provide us

Specific markers for plant breeding

Guide the design of microbial consortium

Identify the prebiotic molecules incorporated

into the granules or seed coating for

inundative microbial application, which

triggers the beneficial activities associated

with particular MAP’s

But, the problem here is most of the root

exudates are considered as public goods by all

microbiota, which presents a high potential

for cross talk A good example of

strigolactones can be taken in this regards

Strigolactones generally act as a signal to

recruit plant beneficial microbes, but they are

also hijacked by pathogens and parasitic

weeds for germination, root attachment and

root infection Thus the development of

mechanism to limit the signal poaching is

important modular microbiome engineering

The key challenges are to,

Understand the complexity of microbial traits

that plant attempts to recruit

Taxonomic distribution in microbiome

Specificity of host signals needed to recruit

the MAP

What can be done to overcome these

challenges?

Signal specificity may be achieved through

precise combination of primary carbon

sources provided in the exudates,

auxotrophies and specialized metabolites that

can act as antimicrobials or as a signal for microbial chemotaxis

Identification of such signals and connecting them to loci in plant genome which can be used in the plant breeding strategies to effectively select for microbiome associated traits

Use of recombinant inbred lines to identify microbiome QTL, especially when provided with metabolic data, which can be harnessed

to connect plant genotypes statistically not only to MAP’s but also to plant metabolites that effectuate them through direct or indirect roles in host selection of microbiota

In conclusion, there is a need for quantitative assessment of the relative contribution of the host genotype, microbiome and environmental conditions for a given phenotype Mathematical MAP’s first approach will provide a more solid basis for engineering microbiome to enhance plant growth and tolerance to a/biotic stresses Identifying the vast and yet unknown functional potential in host associated microbiome and unraveling the dynamic chemical interplay between host and microbiome will be essential to elucidate to what extent and how host recruits or activates members in microbiome for their own benefit.QTL mapping for traits that support PGPR and understanding genetic basis of microbiome assembly can be explored to identify the traits that can be exploited for Augmenting beneficial members of indigenous micro-flora in soil To support and sustain modular microbiome that is introduced into a host system or population

References

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How to cite this article:

Mayur Naitam and Abiraami, T.V 2019 MAP’s Assisted Microbiome Engineering